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Decision brief
GLiNER is ideal for extracting named entities from text with minimal computational resources.
Good fit when
- When you need a lightweight solution for named entity recognition across various languages
- For projects where resource efficiency and fast setup are critical
Avoid when
- If high precision in niche specializations like medical terms or rare proper nouns is required
- In scenarios demanding heavy customization beyond basic named entity recognition capabilities
Observed Jul 14, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Active (7d since push)
- As of 2d
- Provenance
- Not a fork · Personal account
- As of 2d
- Security (OSV)
- 30 low (30 low)
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install GLiNERHow it fits your stack(2)
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Relationship graph
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Similar tools
Same-category neighbours not already linked as typed edges.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
GLiNER is a Python library designed for extracting various entity types from texts using lightweight named entity recognition techniques.
Capability facts
- Languages
- python
Source: github.language+pyproject.toml · Aug 18, 2026
Categories
Graph entities
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Tags
README
Installation
With pip:
pip install gliner
With uv (faster):
uv pip install gliner
With serving support (Ray Serve):
uv pip install gliner[serve] # or: pip install gliner ray[serve]
For agents
This page has a .md twin and JSON over the API.